{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "d:\\softwares\\python\\lib\\site-packages\\umap\\distances.py:1063: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
            "  @numba.jit()\n",
            "d:\\softwares\\python\\lib\\site-packages\\umap\\distances.py:1071: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
            "  @numba.jit()\n",
            "d:\\softwares\\python\\lib\\site-packages\\umap\\distances.py:1086: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
            "  @numba.jit()\n",
            "d:\\softwares\\python\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
            "  from .autonotebook import tqdm as notebook_tqdm\n",
            "d:\\softwares\\python\\lib\\site-packages\\umap\\umap_.py:660: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
            "  @numba.jit()\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "from bertopic import BERTopic\n",
        "from sentence_transformers import SentenceTransformer\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from transformers.pipelines import pipeline\n",
        "from umap import UMAP\n",
        "from hdbscan import HDBSCAN\n",
        "from sklearn.feature_extraction.text import CountVectorizer"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 加载数据"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "条数:  1000\n",
            "预览第一条:  文旅文 创看 洛阳 河南省 文旅文创 发展 大会 本次 大会 安排 项目 签约 主要 方面 内容 一是 文旅 产业 项目 签约 截至 目前 梳理 重点 文旅 项目 投资总额 525.6 亿元 遴选 重大项目 进行 现场 签约 投资总额 365.8 亿元 项目 包括 文物 数字化 开发 文化 创意 园区 建设 文化 项目 涵盖 旅游 度假区 建设 旅游 酒店 民宿 打造 旅游 项目 既有 旅游 景区 开发 商旅 综合体 建设 传统 业态 项目 宇宙 基地 沉浸 演艺 业态 项目 充分体现 我省 文化 旅游 发展 特点 趋势 二是 引客 入豫 项目 签约 主要 我省 文旅 部门 文旅 企业 头部 旅行 知名 OTA 平台 重点 客源地 文旅 部门 签订 引客 入豫 协议 持续 拓展 省外 客源 市场\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# step1 加载文件\n",
        "with open('../../data/切词.txt', 'r', encoding='utf-8') as file:\n",
        "  docs = file.readlines()\n",
        "print('条数: ', len(docs))\n",
        "print('预览第一条: ', docs[0])\n",
        "\n",
        "vectorizer_model = None"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 创建"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Some weights of the model checkpoint at bert-base-chinese were not used when initializing BertModel: ['cls.predictions.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight', 'cls.predictions.decoder.weight']\n",
            "- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(1000, 768)\n"
          ]
        }
      ],
      "source": [
        "# 1. 词向量模型，同时加载本地训练好的词向量\n",
        "embedding_model = pipeline(\"feature-extraction\", model=\"bert-base-chinese\") # 使用bert-base-chinese\n",
        "embeddings = np.load('../../data/embedding_bbc.npy') # 使用bert-base-chinese向量\n",
        "print(embeddings.shape)\n",
        "\n",
        "# 2. 创建分词模型\n",
        "vectorizer_model = CountVectorizer() # 因为我们已经分好词了，所以这里不需要传入分词函数了\n",
        "\n",
        "# 3. 创建UMAP降维模型\n",
        "umap_model = UMAP(\n",
        "  n_neighbors=15,\n",
        "  n_components=5,\n",
        "  min_dist=0.0,\n",
        "  metric='cosine',\n",
        "  random_state=42  # ⚠️ 防止随机 https://maartengr.github.io/BERTopic/faq.html\n",
        ")\n",
        "\n",
        "# 4. 创建HDBSCAN聚类模型\n",
        "# 如果要建设离群值，可以减小下面两个参数\n",
        "# https://hdbscan.readthedocs.io/en/latest/faq.html\n",
        "hdbscan_model = HDBSCAN(\n",
        "  min_cluster_size=40,\n",
        "  min_samples=40,\n",
        ")\n",
        "\n",
        "# 5. 创建CountVectorizer模型\n",
        "vectorizer_model = CountVectorizer(stop_words=['洛阳', '旅游', '文化'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Topic</th>\n",
              "      <th>Count</th>\n",
              "      <th>Name</th>\n",
              "      <th>Representation</th>\n",
              "      <th>Representative_Docs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-1</td>\n",
              "      <td>501</td>\n",
              "      <td>-1_景区_河南_游客_城市</td>\n",
              "      <td>[景区, 河南, 游客, 城市, 洛阳市, 中国, 历史, 活动, 河南省, 发展]</td>\n",
              "      <td>[河南 多家 景区 陆续 发布 开园 公告 台风 杜苏芮 强度 逐渐 减弱 河南 景区 陆续...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>216</td>\n",
              "      <td>0_中国_石窟_龙门石窟_世界</td>\n",
              "      <td>[中国, 石窟, 龙门石窟, 世界, 艺术, 旅行, 景区, 位于, 河南, 历史]</td>\n",
              "      <td>[龙门石窟 中国 石刻 艺术 宝库 现为 世界 文化遗产 全国 重点 文物保护 单位 国家 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>100</td>\n",
              "      <td>1_活动_景区_免费_高速</td>\n",
              "      <td>[活动, 景区, 免费, 高速, 门票, 时间, 白云山, 地点, 期间, 体验]</td>\n",
              "      <td>[洛阳 身边 自驾游 栾川 高速 免费 答疑 自驾游 栾川 高速 费全免 问题 需要 了解 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>99</td>\n",
              "      <td>2_发展_城市_项目_河南</td>\n",
              "      <td>[发展, 城市, 项目, 河南, 文旅, 活动, 中国, 国家, 游客, 建设]</td>\n",
              "      <td>[行走 河南 读懂 中国 关注 全省 文旅文创 发展 大会 二十大 报告 指出 坚持 以文塑...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>42</td>\n",
              "      <td>3_地方_很多_一天_时间</td>\n",
              "      <td>[地方, 很多, 一天, 时间, 已经, 一点, 古城, 酒店, 西安, 感受]</td>\n",
              "      <td>[此次 四天 旅行 已经 结束 以往 不用 这次 大学 同学 一起 毕业 一年 小聚 组团 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4</td>\n",
              "      <td>42</td>\n",
              "      <td>4_旅客_郑州_高速_景区</td>\n",
              "      <td>[旅客, 郑州, 高速, 景区, 客流, 出行, 发送, 通行, 假期, 高峰]</td>\n",
              "      <td>[国庆 长假 我市 迎来 客流 高峰 公路 铁路 发送 旅客 超过 万人次 今年 国庆 长假...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Topic  Count             Name                              Representation  \\\n",
              "0     -1    501   -1_景区_河南_游客_城市  [景区, 河南, 游客, 城市, 洛阳市, 中国, 历史, 活动, 河南省, 发展]   \n",
              "1      0    216  0_中国_石窟_龙门石窟_世界  [中国, 石窟, 龙门石窟, 世界, 艺术, 旅行, 景区, 位于, 河南, 历史]   \n",
              "2      1    100    1_活动_景区_免费_高速   [活动, 景区, 免费, 高速, 门票, 时间, 白云山, 地点, 期间, 体验]   \n",
              "3      2     99    2_发展_城市_项目_河南    [发展, 城市, 项目, 河南, 文旅, 活动, 中国, 国家, 游客, 建设]   \n",
              "4      3     42    3_地方_很多_一天_时间    [地方, 很多, 一天, 时间, 已经, 一点, 古城, 酒店, 西安, 感受]   \n",
              "5      4     42    4_旅客_郑州_高速_景区    [旅客, 郑州, 高速, 景区, 客流, 出行, 发送, 通行, 假期, 高峰]   \n",
              "\n",
              "                                 Representative_Docs  \n",
              "0  [河南 多家 景区 陆续 发布 开园 公告 台风 杜苏芮 强度 逐渐 减弱 河南 景区 陆续...  \n",
              "1  [龙门石窟 中国 石刻 艺术 宝库 现为 世界 文化遗产 全国 重点 文物保护 单位 国家 ...  \n",
              "2  [洛阳 身边 自驾游 栾川 高速 免费 答疑 自驾游 栾川 高速 费全免 问题 需要 了解 ...  \n",
              "3  [行走 河南 读懂 中国 关注 全省 文旅文创 发展 大会 二十大 报告 指出 坚持 以文塑...  \n",
              "4  [此次 四天 旅行 已经 结束 以往 不用 这次 大学 同学 一起 毕业 一年 小聚 组团 ...  \n",
              "5  [国庆 长假 我市 迎来 客流 高峰 公路 铁路 发送 旅客 超过 万人次 今年 国庆 长假...  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "topic_model = BERTopic(\n",
        "  embedding_model=embedding_model,\n",
        "  vectorizer_model=vectorizer_model,\n",
        "  umap_model=umap_model,\n",
        "  hdbscan_model=hdbscan_model,\n",
        ")\n",
        "\n",
        "topics, probs = topic_model.fit_transform(docs, embeddings=embeddings) #传入训练好的词向量\n",
        "topic_info = topic_model.get_topic_info()\n",
        "topic_info"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 减少离群值"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Topic</th>\n",
              "      <th>Count</th>\n",
              "      <th>Name</th>\n",
              "      <th>Representation</th>\n",
              "      <th>Representative_Docs</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-1</td>\n",
              "      <td>41</td>\n",
              "      <td>-1_城市_工作_中国_经济</td>\n",
              "      <td>[城市, 工作, 中国, 经济, 发展, 洛阳市, 考古, 严禁, 河南, 违规]</td>\n",
              "      <td>[河南 多家 景区 陆续 发布 开园 公告 台风 杜苏芮 强度 逐渐 减弱 河南 景区 陆续...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>314</td>\n",
              "      <td>0_中国_河南_石窟_龙门石窟</td>\n",
              "      <td>[中国, 河南, 石窟, 龙门石窟, 历史, 旅行, 艺术, 景区, 世界, 位于]</td>\n",
              "      <td>[龙门石窟 中国 石刻 艺术 宝库 现为 世界 文化遗产 全国 重点 文物保护 单位 国家 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>197</td>\n",
              "      <td>1_景区_活动_门票_时间</td>\n",
              "      <td>[景区, 活动, 门票, 时间, 白云山, 河南, 博物馆, 游客, 免费, 高速]</td>\n",
              "      <td>[洛阳 身边 自驾游 栾川 高速 免费 答疑 自驾游 栾川 高速 费全免 问题 需要 了解 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>285</td>\n",
              "      <td>2_景区_发展_城市_建设</td>\n",
              "      <td>[景区, 发展, 城市, 建设, 项目, 活动, 河南, 游客, 国家, 中国]</td>\n",
              "      <td>[行走 河南 读懂 中国 关注 全省 文旅文创 发展 大会 二十大 报告 指出 坚持 以文塑...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>49</td>\n",
              "      <td>3_地方_很多_已经_一点</td>\n",
              "      <td>[地方, 很多, 已经, 一点, 一天, 博物馆, 时间, 古城, 看到, 今天]</td>\n",
              "      <td>[此次 四天 旅行 已经 结束 以往 不用 这次 大学 同学 一起 毕业 一年 小聚 组团 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4</td>\n",
              "      <td>114</td>\n",
              "      <td>4_景区_年票_旅客_郑州</td>\n",
              "      <td>[景区, 年票, 旅客, 郑州, 游客, 高速, 防控, 疫情, 客流, 假期]</td>\n",
              "      <td>[国庆 长假 我市 迎来 客流 高峰 公路 铁路 发送 旅客 超过 万人次 今年 国庆 长假...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Topic  Count             Name                              Representation  \\\n",
              "0     -1     41   -1_城市_工作_中国_经济   [城市, 工作, 中国, 经济, 发展, 洛阳市, 考古, 严禁, 河南, 违规]   \n",
              "1      0    314  0_中国_河南_石窟_龙门石窟  [中国, 河南, 石窟, 龙门石窟, 历史, 旅行, 艺术, 景区, 世界, 位于]   \n",
              "2      1    197    1_景区_活动_门票_时间  [景区, 活动, 门票, 时间, 白云山, 河南, 博物馆, 游客, 免费, 高速]   \n",
              "3      2    285    2_景区_发展_城市_建设    [景区, 发展, 城市, 建设, 项目, 活动, 河南, 游客, 国家, 中国]   \n",
              "4      3     49    3_地方_很多_已经_一点   [地方, 很多, 已经, 一点, 一天, 博物馆, 时间, 古城, 看到, 今天]   \n",
              "5      4    114    4_景区_年票_旅客_郑州    [景区, 年票, 旅客, 郑州, 游客, 高速, 防控, 疫情, 客流, 假期]   \n",
              "\n",
              "                                 Representative_Docs  \n",
              "0  [河南 多家 景区 陆续 发布 开园 公告 台风 杜苏芮 强度 逐渐 减弱 河南 景区 陆续...  \n",
              "1  [龙门石窟 中国 石刻 艺术 宝库 现为 世界 文化遗产 全国 重点 文物保护 单位 国家 ...  \n",
              "2  [洛阳 身边 自驾游 栾川 高速 免费 答疑 自驾游 栾川 高速 费全免 问题 需要 了解 ...  \n",
              "3  [行走 河南 读懂 中国 关注 全省 文旅文创 发展 大会 二十大 报告 指出 坚持 以文塑...  \n",
              "4  [此次 四天 旅行 已经 结束 以往 不用 这次 大学 同学 一起 毕业 一年 小聚 组团 ...  \n",
              "5  [国庆 长假 我市 迎来 客流 高峰 公路 铁路 发送 旅客 超过 万人次 今年 国庆 长假...  "
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# 减少离群值\n",
        "new_topics = topic_model.reduce_outliers(\n",
        "  docs,\n",
        "  topics,\n",
        "  strategy=\"embeddings\",\n",
        "  embeddings=embeddings, # 应用训练好的Embedding\n",
        "  threshold=0.8 # 可以设置阈值\n",
        ")\n",
        "# 应用更新\n",
        "topic_model.update_topics(docs, topics=new_topics, vectorizer_model=vectorizer_model) # 重新传入vectorizer_model=vectorizer_model\n",
        "topic_info = topic_model.get_topic_info()\n",
        "topic_info"
      ]
    },
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                      "yaxis": {
                        "backgroundcolor": "white",
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                        "gridwidth": 2,
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                        "showbackground": true,
                        "showgrid": false,
                        "showline": true,
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                        "zeroline": false,
                        "zerolinecolor": "rgb(36,36,36)"
                      },
                      "zaxis": {
                        "backgroundcolor": "white",
                        "gridcolor": "rgb(232,232,232)",
                        "gridwidth": 2,
                        "linecolor": "rgb(36,36,36)",
                        "showbackground": true,
                        "showgrid": false,
                        "showline": true,
                        "ticks": "outside",
                        "zeroline": false,
                        "zerolinecolor": "rgb(36,36,36)"
                      }
                    },
                    "shapedefaults": {
                      "fillcolor": "black",
                      "line": {
                        "width": 0
                      },
                      "opacity": 0.3
                    },
                    "ternary": {
                      "aaxis": {
                        "gridcolor": "rgb(232,232,232)",
                        "linecolor": "rgb(36,36,36)",
                        "showgrid": false,
                        "showline": true,
                        "ticks": "outside"
                      },
                      "baxis": {
                        "gridcolor": "rgb(232,232,232)",
                        "linecolor": "rgb(36,36,36)",
                        "showgrid": false,
                        "showline": true,
                        "ticks": "outside"
                      },
                      "bgcolor": "white",
                      "caxis": {
                        "gridcolor": "rgb(232,232,232)",
                        "linecolor": "rgb(36,36,36)",
                        "showgrid": false,
                        "showline": true,
                        "ticks": "outside"
                      }
                    },
                    "title": {
                      "x": 0.05
                    },
                    "xaxis": {
                      "automargin": true,
                      "gridcolor": "rgb(232,232,232)",
                      "linecolor": "rgb(36,36,36)",
                      "showgrid": false,
                      "showline": true,
                      "ticks": "outside",
                      "title": {
                        "standoff": 15
                      },
                      "zeroline": false,
                      "zerolinecolor": "rgb(36,36,36)"
                    },
                    "yaxis": {
                      "automargin": true,
                      "gridcolor": "rgb(232,232,232)",
                      "linecolor": "rgb(36,36,36)",
                      "showgrid": false,
                      "showline": true,
                      "ticks": "outside",
                      "title": {
                        "standoff": 15
                      },
                      "zeroline": false,
                      "zerolinecolor": "rgb(36,36,36)"
                    }
                  }
                },
                "title": {
                  "font": {
                    "color": "Black",
                    "size": 22
                  },
                  "text": "<b>Documents and Topics</b>",
                  "x": 0.5,
                  "xanchor": "center",
                  "yanchor": "top"
                },
                "width": 1200,
                "xaxis": {
                  "visible": false
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                "yaxis": {
                  "visible": false
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              }
            }
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# UMAP可视化\n",
        "reduced_embeddings = UMAP(n_neighbors=10, n_components=2).fit_transform(embeddings)\n",
        "topic_model.visualize_documents(docs, reduced_embeddings=reduced_embeddings, hide_document_hover=True, hide_annotations=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 问题：拿到最新的主题分布"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
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              " 2,\n",
              " 2,\n",
              " 4]"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "topic_model.topics_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 问题：按主题数量重排序"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "   Topic  Count             Name                              Representation  \\\n",
            "1      0    314  0_中国_河南_石窟_龙门石窟  [中国, 河南, 石窟, 龙门石窟, 历史, 旅行, 艺术, 景区, 世界, 位于]   \n",
            "3      2    285    2_景区_发展_城市_建设    [景区, 发展, 城市, 建设, 项目, 活动, 河南, 游客, 国家, 中国]   \n",
            "2      1    197    1_景区_活动_门票_时间  [景区, 活动, 门票, 时间, 白云山, 河南, 博物馆, 游客, 免费, 高速]   \n",
            "5      4    114    4_景区_年票_旅客_郑州    [景区, 年票, 旅客, 郑州, 游客, 高速, 防控, 疫情, 客流, 假期]   \n",
            "4      3     49    3_地方_很多_已经_一点   [地方, 很多, 已经, 一点, 一天, 博物馆, 时间, 古城, 看到, 今天]   \n",
            "0     -1     41   -1_城市_工作_中国_经济   [城市, 工作, 中国, 经济, 发展, 洛阳市, 考古, 严禁, 河南, 违规]   \n",
            "\n",
            "                                 Representative_Docs  \n",
            "1  [龙门石窟 中国 石刻 艺术 宝库 现为 世界 文化遗产 全国 重点 文物保护 单位 国家 ...  \n",
            "3  [行走 河南 读懂 中国 关注 全省 文旅文创 发展 大会 二十大 报告 指出 坚持 以文塑...  \n",
            "2  [洛阳 身边 自驾游 栾川 高速 免费 答疑 自驾游 栾川 高速 费全免 问题 需要 了解 ...  \n",
            "5  [国庆 长假 我市 迎来 客流 高峰 公路 铁路 发送 旅客 超过 万人次 今年 国庆 长假...  \n",
            "4  [此次 四天 旅行 已经 结束 以往 不用 这次 大学 同学 一起 毕业 一年 小聚 组团 ...  \n",
            "0  [河南 多家 景区 陆续 发布 开园 公告 台风 杜苏芮 强度 逐渐 减弱 河南 景区 陆续...  \n"
          ]
        }
      ],
      "source": [
        "sorted_topic_info = topic_info.sort_values(by='Count', ascending=False)\n",
        "print(sorted_topic_info)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 问题：更新主题之后，不能合并主题"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 问题：是否应完全消除离群值"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# 问题：减少离群值的主要策略"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
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